求解非线性互补问题的Modulus-Based变量替换法

本文针对非线性互补问题给出了一种Modulus-based变量替换方法。该方法将非线性互补问题转化为一种非光滑的非线性方程,并提出了相应的迭代算法,在一定条件下,证明了所提出算法的全局收敛。

Modulus-Based Matrix Splitting Iteration Methods for a Class of Stochastic Linear Complementarity Problem

For the expected value formulation of stochastic linear complementarity problem, we establish modulus-based matrix splitting iteration methods. The convergence of the new methods is discussed when the coefficient matrix is a positive definite matrix or a positive semi-definite matrix, respectively. The advantages of the new methods are that they can solve the large scale stochastic linear complementarity problem, and spend less computational time. Numerical results show that the new methods are efficient and suitable for solving the large scale problems.

The Nonlinear Lopsided HSS-Like Modulus-Based Matrix Splitting Iteration Method for Linear Complementarity Problems with Positive-Definite Matrices

In this paper,by means of constructing the linear complementarity problems into the corresponding absolute value equation,we raise an iteration method,called as the nonlinear lopsided HSS-like modulus-based matrix splitting iteration method,for solving the linear complementarity problems whose coefficient matrix in R^(n×n)is large sparse and positive definite.From the convergence analysis,it is appreciable to see that the proposed method will converge to its accurate solution under appropriate conditions.Numerical examples demonstrate that the presented method precede to other methods in practical implementation.

Modulus-Based Multisplitting Iteration Method for a Class of Weakly Nonlinear Complementarity Problem

In this paper,we present a modulus-based multisplitting iteration method based on multisplitting of the system matrix for a class of weakly nonlinear complementarity problem.And we prove the convergence of the method when the system matrix is an H_(+)-matrix.Finally,we give two numerical examples.

A Class of Smoothing Modulus-Based Iterative Method for Solving Implicit Complementarity Problems

In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit complementarity problem into an equivalent implicit fixed-point equation, then introduces a smoothing function to obtain its approximation solutions. The convergence analysis of the algorithm was given, and the efficiency of the algorithms was verified by numerical experiments.

TWO-STEP MODULUS-BASED SYNCHRONOUS MULTISPLITTING ITERATION METHODS FOR LINEAR COMPLEMENTARITY PROBLEMS

To reduce the communication among processors and improve the computing time for solving linear complementarity problems, we present a two-step modulus-based syn- chronous multisplitting iteration method and the corresponding symmetric modulus-based multisplitting relaxation methods. The convergence theorems are established when the system matrix is an H＋-matrix, which improve the existing convergence theory. Numeri- cal results show that the symmetric modulus-based multisplitting relaxation methods are effective in actual implementation.

On the Convergence of Two-Step Modulus-Based Matrix Splitting Iteration Methods for a Restricted Class of Nonlinear Complementarity Problems with H_(+) -Matrices

We propose the two-step modulus-based matrix splitting iteration methods for a class of nonlinear complementarity problems.The corresponding convergence the-ory is established when the system matrix is an H_(+)-matrix.Theoretical analysis gives the choice of parameter matrix involved based on the H-compatible splitting of the sys-tem matrix.Moreover,in actual implementation,the choices of iterative parameters for two-step modulus-based accelerated overrelaxation methods are studied.Numeri-cal experiments show that the method is efficient and further verify the convergence theorems.

Two-Step Two-Sweep Modulus-Based Matrix Splitting Iteration Method for Linear Complementarity Problems

Linear complementarity problems have drawn considerable attention in recent years due to their wide applications.In this article,we introduce the two-step two-sweep modulus-based matrix splitting(TSTM)iteration method and two-sweep modulus-based matrix splitting type II(TM II)iteration method which are a combination of the two-step modulus-based method and the two-sweep modulus-based method,as two more effective ways to solve the linear complementarity problems.The convergence behavior of these methods is discussed when the system matrix is either a positive-definite or an H+-matrix.Finally,numerical experiments are given to show the efficiency of our proposed methods.

The Modulus-Based Levenberg-Marquardt Method for Solving Linear Complementarity Problem

As applying the Levenberg-Marquardt method to the reformulation of linear complementarity problem,a modulus-based Levenberg-Marquardt method with non-monotone line search is established and the global convergence result is presented.Numerical experiments show that the proposed method is efficient and outperforms the modulus-based matrix splitting iteration method.

一种求解非线性互补问题的三项共轭梯度算法

采用Modulus-based变换将非线性互补问题转化为一个非光滑方程组,提出一种三项非线性共轭梯度法,结合某种不用函数值的线搜索技术求解所得的非光滑方程组,从而得到原问题的解.在适当条件下,证明了算法的全局收敛性,数值实验结果表明所提出的算法是有效的.

一种求解非线性互补问题的多步自适应Levenberg-Marquardt算法

本文采用Modulus-based变换将非线性互补问题转化为非光滑方程组,并将一种多步自适应Levenberg-Marquardt方法推广应用于求解所得的非光滑方程组,从而得到原问题的解.在适当条件下,本文证明了算法的全局收敛性.与一种已有的参数自适应Levenberg-Marquardt方法(PSA-LMM)相比较,数值实验结果表明了本文所提出的算法具有更好的效率.